Répartition des espèces
Type of resources
Available actions
Topics
INSPIRE themes
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
status
Service types
Scale
Resolution
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Modelised abundance of species or prediction uncertainty.
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Biologic data have been expressed in abundance (numbers or density values (nbr/km²)) and always required to be log-transformed using a log10(x+1) transformation.
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Biological data have been expressed in abundance (number of individuals per 20 m3).
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Modelised adundance of several species eggs or prediction uncertainty.
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Biologic data have been expressed in abundance (numbers or density values (nbr/km²)) and always required to be log-transformed using a log10(x+1) transformation. Abundance mean (mean) and standard deviation (st) have been calculated.
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Biologic data have been expressed in abundance (numbers or density values (nbr/km²)) and always required to be log-transformed using a log10(x+1) transformation.
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Modelised abundance of species or prediction uncertainty.
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Biologic data have been expressed in abundance (numbers or density values (nbr/km²)) and always required to be log-transformed using a log10(x+1) transformation. Abundance mean (mean) and standard deviation (st) have been calculated. The sum of the kriging error for each yearly kriged abundance fits to the kriging error (v).
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Biologic data have been expressed in abundance (numbers or density values (nbr/km²)) and always required to be log-transformed using a log10(x+1) transformation.
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Abundances were recoded in term of presence-absence. Geostatistical interpolation : the spatial variation of biological data were analysed using GENSTAT (GENSTAT 7 Committee, 2004), which is a GENeral STATistics package including the main geostatistical tools. It computes experimentala variograms, fits these with various authorised mathematical models and uses them to calculate kriged estimates on a fine regular grid (of latitudes and longitudes). The grid of points was imported into ArcMap and interpolated with the Spatial Analyst extension in order to create a continuous raster of 1 km² resolution. The resulting maps illustrate the spatial distributions and the variations over time for biological data studied in CHARM's area. For legends of maps, approximates of the 5th and the 95th quantiles were used for the minimales and maximales values respectively.